Energy, Water & Data: Could Google Make AI Sustainable?

AI is fast becoming one of the most transformative forces of the 21st century, promising new efficiencies, breakthroughs in healthcare and smarter digital experiences. 

However, as this technology evolves, so too do its environmental costs. 

At the centre of this tension sits Google’s report titled The AI Opportunity for Europe’s Climate Goals - a Policy Roadmap.

The tech giant is simultaneously celebrated for its climate commitments and scrutinised for the spiralling environmental footprint of its AI ambitions.

AI’s environmental paradox

Google has long positioned itself as a pioneer in corporate sustainability. 

It became the first major company to reach carbon neutrality in 2007, has matched 100% of its electricity consumption with renewable energy since 2017 and is aiming to operate entirely on carbon-free energy (CFE) by 2030.

Training and running large-scale AI models such as Gemini, Google’s flagship generative AI system, is a key player in Google’s path towards environmental protection.

This system is integrated in a variety of Google products, including Google Earth, Docs and Gmail. 

“Google Earth has democratised geospatial information for a wide range of users and use cases. It renders a 3D representation of Earth, allowing people to explore our planet from endless vantage points,” explains Kate Brandt, Chief Sustainability Officer at Google.

“Businesses utilise its layers to analyse potential renewable energy sites and with new Gemini capabilities, they can ask questions, analyse land data and make informed decisions faster when siting a solar farm.”

However, Gemini requires immense computing power. 

These workloads run across Google’s vast cloud infrastructure, adding significant pressure to already energy-hungry data centres.

“Google’s AI efforts are built on the same infrastructure as its core services,” notes the report, including YouTube, Search and Gmail.

Unlike traditional services, AI models must be trained on huge datasets and require constant updates – intensifying both energy use and water consumption.

Rising emissions vs climate commitments

In 2023, Google’s data centre emissions surged by 48% compared to 2019 levels. 

While the company attributes this to expanded operations and greater cloud usage, experts suggest the rise is closely tied to the growth of AI workloads.

This puts Google in a challenging position. 

While the company frequently touts its leadership in climate innovation and clean energy procurement, critics argue that such claims are undermined by AI-driven growth.

“Google’s AI ambitions are incompatible with its climate goals,” says Fieke Jansen, a researcher at the University of Amsterdam’s DATACTIVE project. 

“You cannot continue to grow your emissions and claim to be on a path to sustainability.”

The transparency gap

One of the most significant concerns is the lack of detailed disclosure on the environmental impact of AI systems. 

Although Google publishes annual sustainability reports, it does not break down the energy or water use associated with individual products or services – especially in its AI use.

This opacity is increasingly problematic as AI becomes deeply integrated into Google’s core offerings. 

In February 2024, the company announced it would embed its Gemini model across Gmail, Google Docs and Android smartphones – vastly expanding AI’s reach and, potentially, its carbon footprint.

“Without disaggregated reporting, there’s no way to verify the impact of AI specifically,” says Fieke. 

“That makes accountability nearly impossible.”

This lack of clarity is not unique to Google. 

Across the tech sector, environmental reporting often lumps AI into broader operational categories, making it difficult for policymakers, researchers and the public to assess its true ecological toll.

Water scarcity and local impact

Alongside energy consumption, water usage is another pressing issue. 

To prevent overheating, data centres frequently rely on evaporative cooling systems that consume vast quantities of water.

In 2021, Google’s data centres used 5.6 billion gallons of water globally. 

This figure is likely to have increased in the years since as AI models and infrastructure are scaled up. 

In regions like The Dalles, Oregon, where Google operates a large data centre, local communities have raised alarms about the pressure on limited water resources, especially during periods of drought.

The combination of high energy use, water dependency and increased heat generation raises significant sustainability challenges – not just globally, but locally.

Sustainable AI

In response to mounting scrutiny, there have been some positive signals from Google and others in the industry. 

In 2023, Google DeepMind launched efforts to improve model efficiency by refining architectures, reducing redundancy in training and using smarter scheduling to minimise energy draw. 

These are steps towards what researchers are calling “green AI” – systems designed to be more environmentally conscious from inception.

However, such initiatives are still in their infancy compared to the rapid pace of AI deployment.

“There is no doubt that AI has enormous potential to help solve global sustainability challenges,” says Fieke. 

“But the way it’s currently being scaled raises serious questions about whether the solution is becoming part of the problem.”

Industry-wide reckoning

Microsoft, Meta and Amazon are all racing to integrate generative AI into their platforms and services, while simultaneously publishing ambitious climate pledges. 

The result is a growing disconnect between digital expansion and environmental stewardship.

As more governments introduce legislation mandating environmental disclosures and lifecycle assessments for digital technologies, tech giants may face increasing pressure to demonstrate not just ambition, but accountability.

The environmental future of AI is not yet written. 

With the right frameworks, transparency and commitment to energy efficiency, it is possible to scale innovation responsibly. 

If companies like Google hope to maintain credibility as climate leaders, they must urgently address the sustainability trade-offs of their AI strategies.

As Fieke warns: “Tech companies can’t rely on offsetting or distant targets. They need to prove their models are sustainable now.”

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